Software Engineer – IICS

• Design, develop, and maintain Informatica PowerCenter and Informatica Intelligent Cloud Services (IICS) solutions for scalable, secure, high-performance enterprise data integration
• Develop and optimize mappings, workflows, reusable transformations, expressions, stored procedures, and ETL pipelines
• Ingest, transform, and load data into data warehouses, data lakes, and operational systems
• Build and support incremental and delta loads, SCD Types 1 and 2, star schema loads, and large-scale batch and near-real-time processing
• Build and maintain REST and web service integrations, service connectors, business services, and IICS Application Integration (CAI) processes and process objects
• Integrate with Salesforce, SAP, ServiceNow, Workday, and other on-premises and cloud platforms
• Install and configure IICS add-on connectors and drivers
• Build file-watching and file-transfer scripts for scheduled and event-driven data exchange
• Optimize SQL performance, database connectivity, task scheduling, and cloud-native deployments on Snowflake, Amazon Redshift, and Google BigQuery
• Implement data quality checks, governance controls, metadata management, lineage, and impact analysis
• Troubleshoot ETL, integration, and pipeline issues, including performance bottlenecks, transformation errors, and data quality anomalies
• Use approved AI tools to draft and review mapping logic, SQL, test data, and technical documentation, and summarize job logs in accordance with Pivotree's AI usage policy
• Record where AI contributed to each change and validate AI-suggested fixes against logs, sample data, and execution plans before production
• Contribute to AI-enabled PIM data enrichment use cases such as attribute extraction, categorization, and content normalization
• Collaborate with data architects, business analysts, and cross-functional teams on integration architectures, reusable patterns, guidelines, and data management improvements
• Communicate project status to management and stakeholders

• 3+ years hands-on experience with IICS Cloud Data Integration (CDI) and Cloud Application Integration (CAI), including mappings, mapping tasks, task flows, schedules, parameter files, transformations, CAI processes, service connectors, and process objects
• 5+ years hands-on experience with Informatica PowerCenter, including mappings, workflows, reusable transformations, stored procedures, and session tuning
• Advanced SQL on Oracle and SQL Server, including complex joins, analytic functions, query tuning, and DDL generation
• Experience with Snowflake, Amazon Redshift, or Google BigQuery loading and performance tuning (preferred)
• Experience with REST APIs and web services using JSON and XML payloads, including authentication and error handling
• Experience integrating Salesforce, SAP, ServiceNow, or Workday
• Knowledge of data warehousing and modeling, including star schemas, SCD Types 1 and 2, incremental loads, and conceptual, logical, and physical data models
• Experience with data quality and lineage tooling
• Experience processing flat files including CSV, delimited, and XML formats
• Experience with file-watching and SFTP transfer scripts
• Unix/Linux shell or DOS scripting experience
• Python for validation and API work (preferred)
• Experience installing IICS add-on connectors and drivers
• Experience with Git, IICS asset management, and promotion across development, test, and production environments
• Working fluency with an approved AI assistant for SQL, mapping logic, scripts, and documentation
• Ability to verify AI output against sample data and execution plans
• Ability to keep client data out of unapproved tools
• Experience building or supporting LLM-based pipeline steps such as enrichment or classification with evaluation and cost monitoring (preferred)
• Ability to learn new technology quickly and adapt to changes in tooling and platforms
• Strong analytical and troubleshooting skills with a systematic approach to root cause analysis
• Clear written and verbal communication with technical and non-technical audiences
• Commitment to documentation, reusable design patterns, and engineering best practices
• Willingness to challenge assumptions, including AI-generated ones, before production